The program will consist of a high-visibility dashboard that links ocean carriers, trucking companies, and railroads as well as retailers, including Walmart, to key hubs like the Port of Los Angeles, the release said.

According to Transportation Secretary Sean Duffy, fewer delays mean lower costs throughout the supply chain, and that this initiative is designed to avoid roadblocks, move freight more quickly, and provide goods at a lower price for the American people.

The American Supply Chain Sovereignty Initiative is modeled after the Freight Logistics Optimization Works program of the department, which was launched in 2022. That data-sharing platform was initially created to facilitate shipment movement after extended Covid-19-related restrictions.

The FLOW platform captures several types of data, and in 2024, the DOT began publishing data on inland freight hubs, such as rail terminal and warehouse end destinations, so as to help shippers with capacity planning and prevent delays in the supply chain. Other published data comprise purchase data as well as cargo movements from specific ports of origin.

As of April 2026, FLOW had 86 members, which included CMA CGM, PetSmart, and The Home Depot as well as GE Appliances.

The new project also builds on the National Freight Strategic Plan that was revised in 2026, according to the press release. The plan, launched in 2020, is meant to steer national policy and investment on supply chains. Duffy is now working to have the legislation needed for the American Supply Chain Sovereignty Initiative included in the 2026 National Defense Authorization Act.

The release confirmed that the Congress is providing the department the framework as well as adaptability to securely simplify national logistics by providing the U.S. Department of Transportation the ability to build role-based access to certain data points.

As supply chains grow in complexity and disruption speeds up, organizations require systems that can react as quickly as circumstances shift. Infios AI enables this with the combination of enterprise knowledge, data in real-time, and intelligent automation so as to turn routine operational signals into coordinated action to sense and act as well as decide in an instant.

According to Richard Stewart, EVP, Product and Industry Strategy at Infios, “With Infios AI, we are embedding intelligence directly into execution workflows, so when conditions change, operations can analyze, recommend, and, increasingly, take action in real time. This is how we help organizations move from reacting to problems to continuously optimizing execution.”

Purpose-built AI use cases bring immediate value

Infios is rolling out a targeted set enhanced AI functionality in warehouse management offering that alleviate the manual coordination as well as operational friction of day-to-day warehouse work, allowing teams to work faster and more reliably:

Intelligent Fault Resolution

Infios AI makes use of live WMS data in order to help warehouse operators quickly detect and fix issues like stalled orders or lost inventory. This provides users with root-cause insight and suggested steps so as to keep warehouse operations running smoothly, decreasing manual intervention and speeding up resolution within current workflows.

• Freeing up experienced staff to perform value-added work
• Saves time spent on investigating errors
• Removes manual, multi-step troubleshooting
• Increases order efficiency and accuracy of inventory

AI Driven Knowledge Assistant

Infios AI integrates product and process knowledge right into the chat interface, so operators can get immediate responses in natural language instead of waiting for supervisor support. It combines product documentation and company-specific operating processes to produce targeted, actionable responses for all operators.

• Reduces manual document research
• Consistent implementation and conformity to operating policies
• Speeds up onboarding and training

Warehouse Associate Development

Infios AI evaluates labor performance data and provides real-time, tailored coaching guidance. It identifies root causes and suggests actionable improvements so supervisors can offer timely feedback without having to do manual research.

• Minimizes manager preparation time
• Offers individualized coaching for every associate
• Consistent guidance enhances workforce productivity

The next generation of warehouse operations is being developed

These innovations bring the vision of Infios of intelligent supply chain execution into the warehouse, changing operations from manual and reactive processes to systems that analyze, recommend, and increasingly take action.

Infios embeds AI directly into the daily workflows so warehouse leaders can transition from data collection, problem investigation, and routine manual intervention to proactive choice-making and effective operations that accelerate productivity at scale. These innovations are a subsequent step in ensuring execution without interruption, pushing real-time, coordinated decision-making more deeply into everyday operations.

It is worth noting that PepsiCo has partnered with Gatik since 2022 and now runs a fleet of 41 autonomous trucks throughout Texas, Arizona as well as Arkansas, confirmed Gatik to Supply Chain Dive in an email.

As per PepsiCo in an email, autonomous trucking, especially on short and repeatable routes, has the ability to help them drive more reliable operations and minimise variability, thereby enabling them to provide a more consistent service experience.

PepsiCo said the deployment of Gatik autonomous trucks happens to be a part of a conscious push to modernize how its products move through its transportation network.

The deal of PepsiCo with Gatik is focused on boosting capacity where it is needed, which will include high-demand regional networks which are indeed hard to staff and essential for keeping shelves full for consumers, the release said.

Gatik said that it is a nuanced, meticulously orchestrated procedure to integrate driverless trucks into a supply chain as intricate as PepsiCo’s, as you can envision.

Gatik further added that safety is our North Star and that they have devoted the time to go through comprehensive safety evaluations and incorporate into supply chain of PepsiCo in a dependable and secure manner.

Interestingly, Gatik’s driverless trucks can very well operate on highways and surface streets when it comes to end-to-end deliveries. They also can alter routes when necessary for complicated regional logistics networks as well as reach numerous pickup and dropoff locations, said the release.The release says that this allows PepsiCo to adjust route plans to daily operational requirements, such as adding or eliminating stops, reacting to demand shifts, and adjusting to levels of activity throughout its distribution centers, said the release.

This adaptability allows PepsiCo to enhance on-time performance and at the same time add capacity without altering its current operations.

PepsiCo has been evaluating new fleet technologies to enhance its transport operations. The organization has also been electrifying its fleet, in addition to autonomous trucks. launch in 2027. PepsiCo has also partnered with shippers such as Ikea and

The company last year said its EV semitrucks will save $1 million in fuel.

The primary driver of this transformation is the need for greater efficiency in an increasingly crowded urban landscape. Traditional delivery methods are often slow and contribute significantly to noise and air pollution. Last mile automation addresses these issues by introducing electric, autonomous solutions that can navigate streets and sidewalks with precision. By removing the need for a human driver for every single delivery, companies can significantly reduce their operating costs while increasing the frequency of their delivery windows. This shift toward logistics innovation is not just about replacing people; it is about creating a more resilient and responsive delivery network that can adapt to the real-time needs of the urban environment.

The Rise of Autonomous Delivery Droids and Sidewalk Robots

One of the most visible forms of last mile automation is the autonomous delivery robot, often referred to as a “sidewalk droid.” These small, six-wheeled vehicles are equipped with an array of sensors, including LiDAR, GPS, and multiple cameras, allowing them to navigate busy urban sidewalks safely. They are designed to travel at walking speeds and can easily avoid pedestrians, pets, and other obstacles. These robots are ideal for “hyper-local” deliveries, such as groceries or restaurant meals, within a 2-3 mile radius of a hub. By handling these short-distance trips, droids free up larger delivery vans for more complex routes, significantly improving the overall throughput of the delivery network.

The beauty of these robots lies in their simplicity and cost-effectiveness. They are electric, meaning they have a near-zero carbon footprint, and their autonomous nature allows them to operate during off-peak hours when traffic is light. This “always-on” capability is a key component of last mile automation, as it allows for a more continuous flow of goods throughout the day. Furthermore, the use of secure, app-based unlocking mechanisms ensures that the package is only accessible to the intended recipient, providing a high level of security and convenience. As these sidewalk robots become more common, we are seeing a shift in how urban logistics is managed, moving away from large, intrusive vehicles and toward a more discrete and efficient model.

Drones and the Future of High-Speed Aerial Delivery

While sidewalk robots handle the ground, delivery drones are taking to the sky to provide even faster last-mile solutions. Drone delivery is particularly effective in areas with difficult terrain or heavy traffic congestion, where a ground vehicle would be significantly delayed. Modern autonomous delivery drones can carry small to medium-sized packages directly from a distribution center to a customer’s yard or a designated drop-off point in a matter of minutes. This “instant gratification” model is a powerful tool for retailers looking to differentiate themselves in a competitive market. The integration of AI-driven route optimization ensures that these drones follow the safest and most efficient flight paths, minimizing their impact on the surrounding community.

However, the widespread adoption of drone delivery faces significant regulatory and technical hurdles. Issues such as airspace management, noise levels, and privacy must be addressed before drones can become a standard part of the delivery ecosystem. Despite these challenges, the potential benefits are too great to ignore. Drones represent a major leap forward in last mile automation, offering a level of speed and agility that no ground-based solution can match. We are already seeing successful pilot programs in rural and suburban areas, and as the technology matures and regulations evolve, it is only a matter of time before drones become a common sight in the urban skyline, delivering everything from life-saving medicines to the latest tech gadgets.

AI-Driven Route Optimization and the Smart Delivery Network

Behind the physical robots and drones is the “digital brain” that makes it all possible: AI-driven route optimization. This software is the true engine of last mile automation, processing massive amounts of data to ensure that every delivery is as efficient as possible. Unlike traditional routing software, which is often static, AI-powered systems are dynamic and predictive. They can account for real-time traffic updates, weather conditions, and even the availability of specific delivery slots at a customer’s location. This level of intelligence allows for “dynamic rerouting,” where the system can adjust a vehicle’s path mid-trip to avoid a sudden bottleneck, ensuring that the delivery window is always met.

Furthermore, this software enables a more connected and transparent delivery experience for the customer. Through integrated platforms, customers can track their delivery in real-time, receive accurate arrival estimates, and even communicate directly with the delivery system to change their drop-off preferences. This focus on the customer experience is a critical part of logistics innovation, as it builds trust and loyalty in a world where convenience is king. The combination of physical automation and digital intelligence is what defines a “smart” delivery network, one that is not only efficient but also highly responsive to the needs of the people it serves.

In conclusion, last mile automation is the key to unlocking a more efficient and sustainable future for urban logistics. By embracing autonomous solutions and AI-driven intelligence, companies can overcome the traditional challenges of the final leg of the journey, providing a faster and more reliable service to their customers. The transition to an automated last mile is an ongoing process that requires significant investment in technology and a willingness to navigate complex regulatory environments. However, the rewards in terms of lower costs, higher customer satisfaction, and a smaller environmental footprint make it one of the most exciting opportunities in the logistics industry today. The era of the human-driven delivery van is evolving, and the future of the last mile is autonomous, intelligent, and closer than we think.

The primary advantage of cloud logistics is the ability to achieve a “single source of truth.” In a traditional supply chain, different partners manufacturers, carriers, warehouse operators, and retailers often use disparate systems that do not communicate well with each other. This leads to delays, errors, and a general lack of visibility. Cloud-based platforms, however, act as a centralized hub where all stakeholders can access and update the same data in real-time. This level of connectivity ensures that everyone is working from the same set of facts, allowing for better coordination and faster decision-making. In a world where a single delay at a port can have a global ripple effect, the ability to share information instantly is the bedrock of a resilient and connected supply chain.

Scalability and Flexibility in a Volatile Marketplace

One of the most compelling reasons for adopting cloud based logistics platforms is the inherent scalability they offer. The logistics industry is notoriously cyclical, with massive spikes in demand during holiday seasons followed by quieter periods. Traditional on-premise software requires companies to invest in expensive hardware and infrastructure that may sit idle for much of the year. In contrast, SaaS logistics models allow businesses to scale their computing power and software capabilities up or down based on their current needs. This “pay-as-you-grow” approach significantly reduces capital expenditures and ensures that even small and medium-sized enterprises can access the same advanced tools as the industry giants.

This flexibility extends to the ability to integrate new technologies quickly. Cloud-based platforms are designed to be “open,” using APIs (Application Programming Interfaces) to connect with a wide range of third-party applications. This means that a company can easily add a new AI-driven route optimization tool, a blockchain-based tracking system, or a suite of IoT sensors to their existing network without having to overhaul their entire IT infrastructure. This “plug-and-play” capability allows for a more modular approach to supply chain platforms, ensuring that the organization can always stay at the cutting edge of logistics innovation. The cloud acts as the operating system for the smart network, providing the foundation for a truly agile business model.

Enhancing Global Visibility and Collaborative Decision-Making

The global nature of modern trade means that a supply chain is only as strong as its weakest link. Cloud based logistics platforms bridge the geographical gaps between partners, providing real-time visibility into the movement of goods across borders. Whether it is a container on an ocean vessel or a small parcel on a delivery van, the status of every asset is visible through a single digital interface. This transparency is crucial for managing the complexities of international logistics, where customs clearances, weather disruptions, and port congestion are constant challenges. By having a clear view of the entire network, logistics managers can proactively identify potential issues and reroute shipments before they become major problems.

Furthermore, these platforms foster a more collaborative approach to decision-making. In a connected supply chain, partners can share more than just tracking numbers; they can share insights and forecasts. For example, a retailer can share real-time sales data with their suppliers through a shared cloud platform, allowing the supplier to adjust their production schedules based on actual demand rather than just historical estimates. This “synchronized supply chain” reduces the need for large safety stocks and minimizes the risk of stockouts or overstocking. The cloud transforms logistics from a series of handoffs into a collaborative partnership where every participant is working toward a common goal of efficiency and customer satisfaction.

Security, Resilience and the Future of Digital Logistics

As more of the supply chain moves to the cloud, the issue of cybersecurity becomes paramount. Leading cloud based logistics platforms invest heavily in state-of-the-art security measures, including multi-factor authentication, end-to-end encryption, and continuous monitoring. These measures often provide a higher level of protection than what an individual company could achieve with an on-premise system. Furthermore, cloud platforms offer superior resilience through built-in redundancy and disaster recovery capabilities. If one data center goes down, the system can automatically switch to another, ensuring that the supply chain remains “always-on.” This reliability is essential for maintaining trust in a world where digital disruptions can be just as damaging as physical ones.

Looking ahead, the evolution of cloud based logistics platforms will be driven by the deeper integration of artificial intelligence and machine learning. We are moving toward “autonomous” smart networks, where the platform itself can identify patterns, predict disruptions, and execute corrective actions without human intervention. The cloud will not just be a place to store data; it will be an intelligent engine that actively manages the flow of goods around the world. As we continue to refine these systems, the distinction between “logistics” and “technology” will continue to fade, leading to a more efficient, transparent, and sustainable global economy. The cloud is the sky in which the future of logistics will be written, and for those who embrace it, the possibilities are limitless.

In conclusion, cloud-based logistics platforms are the essential infrastructure for the next generation of supply chain management. By providing a platform for connectivity, scalability, and collaboration, they are helping businesses overcome the challenges of a fragmented and volatile marketplace. The transition to the cloud is a strategic journey that requires a commitment to digital transformation and a willingness to embrace new ways of working. However, the rewards in terms of greater agility, lower costs, and enhanced customer satisfaction make it a journey well worth taking. As the industry moves forward, the companies that thrive will be those that view the cloud not just as a tool, but as the foundation of their smart network. The era of digital logistics is here, and it is powered by the cloud.

To understand why AMR robots are so revolutionary, one must first distinguish them from Automated Guided Vehicles (AGVs). AGVs have been around for years, but they are fundamentally limited by their need for a fixed path. If an obstacle is placed in their way, an AGV simply stops and waits for it to be removed. In contrast, an AMR uses sophisticated mapping technology often LiDAR or 3D cameras—to understand its surroundings in real-time. If an AMR encounters a stray pallet or a group of workers, it can calculate a safe path around them and continue its mission. This level of autonomy makes AMRs ideal for the “chaos” of a modern warehouse, where layouts change frequently and human activity is constant. This flexibility is the primary reason why warehouse robotics has moved from a niche experiment to a core operational strategy for global logistics leaders.

Scalability and Flexibility in the Modern Distribution Center

One of the most compelling advantages of autonomous mobile robots warehousing is the inherent scalability they offer. In a traditional automated warehouse, the infrastructure is often fixed. Installing a massive conveyor system or an automated storage and retrieval system (AS/RS) requires a significant upfront investment and months of installation time. Once in place, these systems are difficult to move or expand. AMRs, however, require no changes to the physical infrastructure of the building. A warehouse can start with just a few robots and add more as their volume increases or as peak seasons approach. This “automation as a service” model allows companies to manage their capital expenditures more effectively while ensuring they always have the capacity to meet demand.

This flexibility extends to the tasks the robots can perform. Modern warehouse automation trends show a move away from single-purpose machines. Today’s AMR robots can be outfitted with various attachments, such as shelving units, conveyor tops, or robotic arms, allowing them to handle everything from small parcels to heavy pallets. This versatility means that a single fleet of robots can be repurposed throughout the day. In the morning, they might be used for inbound receiving and put-away; by the afternoon, they could be transitioned to support picking and packing operations. This high utilization rate maximizes the return on investment and ensures that the robots are always contributing to the facility’s overall throughput.

Revolutionizing Automated Picking Systems and Order Accuracy

The picking process is often cited as the most labor-intensive and error-prone part of warehouse operations. Traditional “man-to-goods” picking involves workers walking miles every day to find items on shelves, a process that is both exhausting and inefficient. Autonomous mobile robots warehousing changes this by enabling “goods-to-person” or collaborative picking workflows. In a goods-to-person setup, AMRs bring entire racks of products directly to a stationary workstation where a human operator selects the necessary items. This eliminates travel time entirely, allowing a single worker to do the work of three or four in a manual environment. The impact on automated picking systems is profound, as it simultaneously increases speed while drastically reducing the fatigue that often leads to errors.

In collaborative picking models, the robot follows the worker as they move through the aisles. The AMR acts as a smart cart, carrying the picked items and indicating which slot they should be placed in. Once the order is complete, the robot autonomously navigates to the packing station, while another robot takes its place behind the worker. This seamless flow keeps the human picker in the “active” zone for a higher percentage of their shift. Because the robots are integrated with the warehouse management system, they provide real-time validation of every pick. If a worker grabs the wrong item, the robot can provide an immediate alert, ensuring that order accuracy remains near 100%. This level of precision is critical in an era where the cost of a “mis-pick” includes not just the shipping error, but also the potential loss of customer loyalty.

The Human-Robot Collaborative Environment and Safety

A common concern when introducing robotics in logistics is the impact on the existing workforce. However, the design philosophy behind AMRs is centered on collaboration rather than replacement. These robots are built with safety as a top priority. They are equipped with multiple redundant sensors that allow them to detect a human foot or an outstretched arm from several meters away, slowing down or stopping instantly if a collision is imminent. This “soft” interaction allows humans and robots to share the same space safely, creating a hybrid environment where each can do what they do best. Robots handle the repetitive, heavy, and boring tasks, while humans provide the dexterity, problem-solving skills, and oversight required for complex operations.

Looking ahead, the evolution of autonomous mobile robots warehousing will likely focus on even deeper integration and increased intelligence. We are already seeing the emergence of “swarm intelligence,” where a fleet of robots can communicate with each other to optimize their collective movements and avoid congestion. Furthermore, the integration of AI-driven grasping technology will allow AMRs to not only transport goods but also pick them up directly from the shelves, moving closer to the goal of a fully autonomous “lights-out” warehouse. As technology continues to advance, the distinction between different types of automation will blur, leading to a unified, intelligent, and highly responsive logistics ecosystem.

In conclusion, autonomous mobile robots are much more than just a way to move boxes. They are a fundamental tool for building a modern, resilient supply chain. By providing flexibility, scalability, and unmatched precision, AMRs are helping businesses overcome the challenges of labor shortages and rising consumer expectations. The transition to a robot-enhanced warehouse is not just about staying competitive; it’s about creating a better working environment and a more efficient world. As these warehouse automation trends continue to gain momentum, the organizations that embrace mobile robotics will be the ones that lead the way in the next era of global distribution. The transformation is already underway, and the robots are leading the charge.

The core strength of AI in logistics lies in its capacity for predictive analytics. In a traditional setting, supply chain managers often find themselves reacting to events after they have occurred a late shipment, a sudden spike in demand, or a weather-related delay. Predictive analytics supply chain models change this dynamic by using machine learning algorithms to analyze historical data and external variables. These systems can predict with high accuracy when a port might become congested or when a specific region might experience a surge in orders. By having this foresight, companies can adjust their smart logistics operations in advance, rerouting shipments or increasing inventory levels to mitigate potential issues. This proactive stance significantly reduces lead times and ensures that the flow of goods remains steady even in the face of volatility.

Precision Routing and the Optimization of the Last Mile

One of the most visible applications of AI driven logistics operations is in the field of route optimization. The “last mile” of delivery is notoriously the most expensive and inefficient part of the supply chain, often accounting for a disproportionate percentage of total shipping costs. Artificial intelligence tackles this challenge by considering a multitude of factors in real-time, including traffic patterns, delivery windows, vehicle capacity, and even fuel efficiency. Unlike traditional routing software that follows a set logic, AI-powered systems are dynamic. They can update a driver’s route mid-trip based on new information, ensuring that every mile driven is as productive as possible. This level of logistics optimization not only saves time and money but also reduces the carbon footprint of the delivery fleet, aligning business goals with environmental sustainability.

Furthermore, the integration of real time visibility into these operations provides a level of transparency that has become a requirement for modern consumers. In an era where customers expect to know the exact location of their package at any given time, AI acts as the bridge between raw tracking data and actionable information. Smart logistics operations use AI to filter out the noise and provide stakeholders with meaningful updates. If a delay is inevitable, the system can automatically communicate this to the customer while simultaneously identifying the root cause and suggesting a solution. This transparency builds trust and allows for better coordination across the entire distribution network, from the warehouse floor to the customer’s doorstep.

Enhancing Supply Chain Resilience Through Risk Management

Beyond daily operational gains, AI driven logistics operations play a critical role in strategic risk management. The global supply chain is susceptible to a wide range of disruptions, from geopolitical tensions to natural disasters. AI systems can perform “what-if” simulations on a massive scale, allowing companies to test the resilience of their networks under various stress scenarios. For example, a company might use AI to model the impact of a major factory closure in a specific region. The system can then identify alternative suppliers and calculate the cost and time implications of switching routes. This ability to model complex contingencies enables businesses to build “buffer” into their systems where it is needed most, ensuring that they can pivot quickly when a real crisis strikes.

Moreover, AI is revolutionizing the way inventory is managed across complex networks. Intelligent systems can optimize stock levels at multiple locations simultaneously, ensuring that the right products are in the right place at the right time without overstocking. This balancing act is crucial for maintaining healthy cash flow. By analyzing consumer behavior and market trends, AI can suggest where to hold inventory to minimize shipping distances and maximize fulfillment speed. This localized approach to distribution, supported by smart logistics operations, is a key differentiator for companies looking to compete in a world where “same-day delivery” is increasingly the standard.

The Human Element and the Evolution of Logistics Talent

As AI becomes more deeply embedded in logistics, the role of the human professional is also evolving. There is a common misconception that AI will replace the need for human expertise in the supply chain. In reality, the most successful implementations are those that combine the computational power of AI with human judgment and creativity. While AI can handle the data-crunching and routine decision-making, humans are needed to manage relationships, negotiate complex contracts, and handle the ethical considerations that come with automated systems. The future of the industry lies in a “human-in-the-loop” model, where AI driven logistics operations empower professionals to focus on high-level strategy rather than administrative tasks.

In conclusion, the impact of artificial intelligence on the supply chain is both broad and deep. From the micro-optimization of a single delivery route to the macro-forecasting of global trade flows, AI is the common thread that connects modern logistics. The transition to AI driven logistics operations is an ongoing process that requires investment in both technology and talent. However, the rewards greater efficiency, lower costs, and enhanced customer satisfaction make it one of the most compelling opportunities in the business world today. As we move forward, the companies that successfully harness the power of AI will be the ones that define the future of global commerce, creating a supply chain that is not just a sequence of movements, but a highly intelligent and responsive ecosystem.

The journey toward full integration of AI in logistics is not without its hurdles. Issues such as data silos, legacy systems, and the need for standardized communication protocols must be addressed. Yet, the momentum is undeniable. Every year, the algorithms become more sophisticated, the sensors become more ubiquitous, and the business case for AI becomes more airtight. By focusing on predictive analytics supply chain solutions and fostering a culture of innovation, the logistics industry is setting the stage for a new era of global connectivity. The result will be a more transparent, efficient, and sustainable world for businesses and consumers alike, proving that when it comes to the supply chain, the smartest route is the one powered by AI.

It is worth noting that the award emphasises Persistent’s potential to modernise supply chain operations on Google Cloud in order to assist enterprises in enhancing their visibility, speeding up decision-making and implementing AI-driven features within the production settings.

Apparently, the manufacturing and retail companies are re-architecting their supply chains to be more robust and smarter. Legacy systems and different information still hamper transparency and slow decision-making along with limiting the automation. Persistent tackles these issues by modernizing core systems within the Google Cloud platform in order to build a centralised, cloud-native database that enables intelligent orchestration throughout planning and inventory as well as logistics operations.

This foundation allows organisations to apply AI all over the supply chain lifecycle, comprising demand forecasting, inventory optimisation, logistics management as well as exception resolution by way of integrated data platforms and automation as well as intelligent agents.

Persistent leverages the AI stack from Google Cloud, including Gemini, to empower the implementation of agentic and GenAI capabilities when it comes to production, enabling enterprises to move from insights to autonomous actions to ongoing optimisation, which results in responsive, data-driven supply chain processes.

This recognition is based on proven customer impact, implementation strength and compatibility with the strategic priorities of Google Cloud and highlights Persistent’s innovation and specialised technical knowledge in dealing with the particular challenges of the supply chain and logistics industry on Google Cloud.

It solidifies the leadership position of the company as the dependable partner and ecosystem orchestrator of preference, integrating deep engineering knowledge with a unique AI-first methodology to modernize intricate enterprise environments via cloud-native architectures and automation as well as infrastructure-as-code, executed at scale with minimal downtime. It also showcases the leadership by Persistent in AI-first execution with Gemini Enterprise so as to address logistics and supply chain challenges.

Apparently, the long-standing partnership of Persistent with Google Cloud continues to drive co-innovation as well as go-to-market efforts to accelerate AI-led supply chain transformation throughout industries. With almost 20 years of experience, Persistent is a premier Google Cloud Partner, delivering enterprise-scale change in all industries with reliability and speed. They have over 50 areas of Google Cloud expertise, multiple partner specialisations, and in excess of 2,000 Google Cloud certifications.

The expansion addresses rising demand across the cross-border supply chain. Mexico’s export growth continues to accelerate, boosted by advances in the main producing regions. In Chihuahua, which is just across from El Paso, exports were $47.551 billion in the second quarter of 2025, approximately 36% higher than the same period a year ago.  Much of that surge comes from high-tech goods, especially computer and communication equipment, which continue to anchor the region’s role as a major manufacturing hub.

Jay Cornmesser, Vice President for Mexico Cross-Border Services at C.H. Robinson, highlighted the vital role of the area. “We continue to see El Paso emerge as a vital gateway for not just high-tech freight, but also automotive, medical devices, and healthcare products,” Cornmesser said. He noted that Juárez, located just across the border, maintains a substantial maquiladora manufacturing base. “Our expansion in El Paso is a direct response to the evolving needs of our customers in today’s dynamic trade landscape.” The necessity for this added capacity was driven by growth in both nearshoring and overall freight volume, highlighting the pressure on the entire cross-border supply chain.

Cornmesser, speaking to Logistics Management, emphasized the dramatic increase in trade volume, citing that Mexico’s exports had jumped over 13% from last year, with Chihuahua leading the way due to its nearly 36% rise in export value. He confirmed that industries like tech, automotive, and medical devices are primarily driving this increased volume and require logistics support that can keep pace and scale. The company believes having this extra capacity in the El Paso Logistics Hub, near the Juárez manufacturing hub and the booming activity from Chihuahua, gives shippers a major advantage.

The ultimate goal, according to Michael Castagnetto, president of North American Surface Transportation at C.H. Robinson, is to give shippers more flexibility when global trade remains unpredictable. The new capacity supports businesses of all sizes, including those that are first-time market entrants requiring assistance with customs, transportation, local requirements, and warehousing. “With 35+ years of proven expertise in Mexico, boots on the ground, AI-driven solutions, and 2 million square feet of strategically located facilities on the border, we set the standard for end-to-end service,” he said. “We’re not just reacting to change—we’re anticipating it.” This investment solidifies C.H. Robinson’s leadership in the North American cross-border supply chain.

C.H. Robinson, the leader in Lean AI supply chains, has been named to the 2026 FreightTech 25, which recognizes the most innovative companies transforming transportation and logistics through technology.

C.H. Robinson was initially named to this year’s FreightTech 100, a list of innovators chosen by a FreightWaves panel. From that list, more than 80 judges including CEOs, investors, academics and industry leaders each ranked their top 25 selections.

C.H. Robinson earned its place on this year’s FreightTech 25 list for its industry-leading use of agentic AI across global supply chains. Over the past year, the company has:

• Grown its fleet of AI agents past 30: The fleet of AI agents performs millions of increasingly complex shipping tasks, from price quotes to orders to setting appointments for pickup and delivery to tracking.
• Launched the Always-On Logistics Planner™: Embedded in customers’ operations, it operates 24/7 to improve speed, accuracy, and reliability across their supply chains.
• Introduced the Agentic Supply Chain^™: An intelligent ecosystem that goes beyond automation, continuously thinking, learning and acting in real time to optimize performance at a global scale. Businesses can plug into C.H. Robinson and immediately benefit from the company’s agentic AI capabilities.

AI has also played a key role in C.H. Robinson’s transformation, drawing positive commentary from analysts across the investment community. Reports from 16 leading firms underscore how the company’s AI-driven innovation and disciplined execution set it apart, delivering real-world results at a scale few others in logistics or in any industry have achieved with AI.

At the core of this transformation strategy are three unique strengths: industry-leading AI technology, the world’s best logisticians, and a Lean operating model that drives continuous improvement. Lean AI is the company’s rigorous, purpose-built approach to artificial intelligence. It maximizes customer value and enables smarter, faster, and better supply chains.

With its Lean AI approach, C.H. Robinson’s technology automates tens of thousands of logistics tasks every day, empowering its employees to focus on solving complex challenges for its 83,000 customers and 450,000 contract carriers. These capabilities have produced measurable results, including a greater than 40% productivity boost, millions of shipping tasks performed by agentic AI, and significant time and cost savings.

With seven consecutive quarters of outperforming the market and a growing portfolio of AI-driven solutions, C.H. Robinson is demonstrating what practical, measurable innovation looks like at scale. While others in the industry are still experimenting with AI, the company is already transforming how global supply chains operate.